关键词: 分类, 神经网络, 覆盖算法, 学习向量量化（LVQ）

Abstract: Covering algorithm is a classification algorithm with constructive neural network of high accuracy and strong generalization ability. According to the arbitrariness of the selections of cover center, combining competitive neural network method, an improved algorithm of covering algorithm is proposed. Before learning covering algorithm, learning center samples of the sample set as cover centers are selected by LVQ to optimize covering spherical. In the experiment in the test data standard UCI, comparing two parameters：classification accuracy and the covering number, the result of experiments shows that the proposed method is effective.

Key words: classification, neural network, covering algorithm, Learn Vector Quantization（LVQ）